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Arabic summarization in Twitter social network

(in lingua inglese)

In this paper, a machine learning based summarization system for summarizing Arabic posts in Twitter social network has been introduced. In the system, the problem was formulated as regression problem, using model tree, instead of a binary classification based problem. The proposed strategy is evaluated and the results are compared with that obtained by the well-known multi document summarization algorithms including; SumBasic, TF-IDF, PageRank, MEAD, and human summaries. Using the F measure evaluation method, the proposed system provides best results of 50% compared to the manual summarization of 53%.

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Articoli tecnico scientifici o articoli contenenti case history
Articolo Ain Shams Engineering Journal, 2014




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